tensorflow 2.8.0

• Updated default Tensorflow version installed by install_tensorflow() to 2.8.

• as_tensor() gains a shape argument, can be used to fill or reshape tensors. Scalars can be recycled to a tensor of arbitrary shape, otherwise supplied objects are reshaped using row-major (C-style) semantics.

• install_tensorflow() now provides experimental support for Arm Macs, with the following restrictions:

  • “conda” is the only supported installation method.
  • requests for non-default or older tensorflow versions are not supported.

• install_tensorflow() default conda_python_version changes from 3.7 to NULL.

• tf.TensorShape()’s gain format() and print() S3 methods.

• [ method for slicing tensors now accepts NA as a synonym for a missing or NULL spec. For example x[NA:3] is now valid, equivalent to x[:3] in Python.

tensorflow 2.7.0

• Default Tensorflow version installed by install_tensorflow() updated to 2.7

• Breaking changes:

  • shape() now returns a tf.TensorShape() object (Previously an R-list of NULLs or integers).
  • [ method for tf.TensorShape() objects also now returns a tf.TensorShape(). Use [[, as.numeric, as.integer, and/or as.list to convert to R objects.
  • length() method for tensorflow.tensor now returns NA_integer_ for tensors with not fully defined shapes. (previously a zero length integer vector).
  • dim() method for tensorflow.tensor now returns an R integer vector with NA for dimensions that are undefined. (previously an R list with NULL for undefined dimension)

• New S3 generics for tf.TensorShape()’s: c, length, [<-, [[<-, merge, ==, !=, as_tensor(), as.list, as.integer, as.numeric, as.double, py_str (joining previous generics [ and [[). See ?shape for extended examples.

• Ops S3 generics for tensorflow.tensors that take two arguments now automatically cast a supplied non-tensor to the dtype of the supplied tensor that triggered the S3 dispatch. Casting is done via as_tensor(). e.g., this now works: as_tensor(5L) - 2 # now returns tf.Tensor(3, shape=(), dtype=int32) previously it would raise an error: TypeError: `x` and `y` must have the same dtype, got tf.int32 != tf.float32 Generics that now do autocasting: +, -, *, /, %/%, %%, ^, &, |, ==, !=, <, <=, >, >=

• install_tensorflow(): new argument with default pip_ignore_installed = TRUE. This ensures that all Tensorflow dependencies like Numpy are installed by pip rather than conda.

• A message with the Tensorflow version is now shown when the python module is loaded, e.g: “Loaded Tensorflow version 2.6.0”

tensorflow 2.6.0

• Updated default Tensorflow version to 2.6.

• Changed default in tf_function() to autograph=TRUE.

• Added S3 generic as_tensor().

• tfautograph added to Imports

• jsonlite removed from Imports, tfestimators removed from Suggests

• Refactored install_tensorflow().

  • Potentially breaking change: numeric versions supplied without a patchlevel now automatically pull the latest patch release. (e.g. install_tensorflow(version="2.4") will install "2.4.2". Previously it would install “2.4.0”)

• Removed “Config/reticulate” declaration from DESCRIPTION.

  • Setting RETICULATE_AUTOCONFIGURE=FALSE environment variable when using non-default tensorflow installations (e.g., ‘tensorflow-cpu’) no longer required.
  • Users will have to call install_tensorflow() for automatic installation.

• Refactored automated tests to closer match the default installation procedure and compute environment of most user.

• Expanded CI test coverage to include R devel, oldrel and 3.6.

• Fixed an issue where extra packages with version constraints like install_tensorflow(extra_packages = "Pillow<8.3") were not quoted properly.

• Fixed an issue where valid tensor-like objects supplied to log(x, base), cospi(), tanpi(), and sinpi() would raise an error.

tensorflow 2.5.0

• Updated default Tensorflow version to 2.5.
• Added support for additional arguments in tf_function() (e.g., jit_compile)
• Added support for expm1 S3 generic.
• tfe_enable_eager_execution is deprecated. Eager mode has been the default since TF version 2.0.
• Improved error message in tf_config() on unsuccessful installation.

tensorflow 2.4.0

• Fixed error with use_session_with_seed (#428)
• Added a new set_random_seed function that makes more sense for TensorFlow >= 2.0 (#442)
• Updated the default version of TensorFlow to 2.4 as well as the default Python to 3.7 (#454)

TensorFlow 2.2.0 (CRAN)

• Bugfix with all_dims (#398)

• Indexing for TensorShape & py_to_r conversion (#379, #388)

TensorFlow 2.0.0 (CRAN)

• Upgraded default installed version to 2.0.0.

• Tensorboard log directory path fixes (#360).

• Allow for v1 and v2 compat (#358).

• install_tensorflow now does not installs tfprobability, tfhub and other related packages.

TensorFlow 1.14.1 (CRAN)

• Upgraded default installed version to 1.14.0

• Refactored the install_tensorflow code delegating to reticulate (#333, #341): We completely delegate to installation to reticulate::py_install, the main difference is that now the default environment name to install is r-reticulate and not r-tensorflow.

TensorFlow 1.13.1 (CRAN)

• added option to silence TF CPP info output

• tf_gpu_configured function to check if GPU was correctly